A New Question Answering System for the Arabic Language

Abstract

We depict the architecture of a question answering system and methodically evaluate contributions of different system components to accuracy. The system differs from most question answering systems in its dependency on data redundancy rather than complicated linguistic analyses of either questions or contender answers. Because a wrong answer is often worse than no answer. A Question Answering (QA) system is a system that takes natural language questions expressed in the Arabic language then attempts to provide short answers. In order to handle this problem, traditional information retrieval techniques joined with a sophisticated natural language processing approach have been used in this research work. Using keyword matching, simple structures extracted from both the question and the candidate documents selected by the IR system were used in the process of identifying the answer. In order to perform this process, we used an existing tagger to identify proper names and other crucial lexical items and build lexical entries. Also provide an analysis of Arabic question forms and attempt to formulate better kinds of answers that users find more appropriate.